Compatible taper function for Scots pine plantations in northwestern Spain
Bibliographic record
Abstract
A compatible system for estimation of individual tree volume was developed for Scots pine (Pinus sylvestris L.) in northwestern Spain. The system comprises a merchantable volume equation, a total volume equation, and a taper function. The use of the volume equation allows rapid estimation of tree volume, and stand volume by summing individual tree volumes, which is equal to the volume obtained by integrating the taper equation. The volume equation is very easy to use and is therefore preferred when classification of the products by merchantable sizes is not required. Data from 228 destructively sampled trees were used for model development. Fourteen compatible volume equations were evaluated, 13 of these equations were taken from the available literature, and the other was developed in the present study. A modified second-order continuous autoregressive error structure was used to correct the autocorrelation of the hierarchical data used. The model developed by Fang et al. (Z. Fang, B.E. Borders, and R.L. Bailey. 2000. For. Sci. 46: 112) best described the data. There model is therefore recommended for the estimation of diameter at a specific height, merchantable volume, and total volume of Scots pine stems in the area of study.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".